NVIDIA
Senior Solutions Architect, Data Processing
NVIDIA, California, Missouri, United States, 65018
Senior Solutions Architect, Data Processing
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Senior Solutions Architect, Data Processing
role at
NVIDIA .
NVIDIA is currently seeking a Solutions Architect for High-Performance Databases. You will research new algorithms and memory management techniques to accelerate databases on modern computer architectures, investigate hardware and system bottlenecks, and optimize performance of data-intensive applications. This role sits at the forefront of technology, providing visibility and impact to a leader like NVIDIA.
NVIDIA has continuously reinvented itself over two decades, starting with the GPU in 1999 that sparked the PC gaming market and revolutionized parallel computing. As a learning machine, NVIDIA constantly evolves to tackle hard problems and amplify human imagination and intelligence.
What You Will Be Doing
Research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications.
Work directly with other technical experts in industry and academia to perform in-depth analysis and optimization of complex data-intensive workloads, ensuring the best possible performance on current GPU architectures.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tool teams at NVIDIA.
Collaborate with industry and academic partners to push the bounds of data processing using NVIDIA’s full product line.
What We Need To See
Masters or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree, or equivalent experience.
8+ years of experience.
Programming fluency in C/C++ with a deep understanding of algorithms and software design.
Hands‑on experience with low-level parallel programming (e.g., CUDA preferred, OpenACC, OpenMP, MPI, pthreads, TBB).
In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
Domain expertise in high-performance databases, ETL, data analytics, and/or vector database.
Good communication and organization skills with a logical approach to problem solving and prioritization.
Ways To Stand Out From The Crowd
Experience optimizing/implementing database operators or query planners, especially for parallel or distributed frameworks (e.g., production database or Spark).
Background with optimizing vector database index build and/or search.
Experience profiling and optimizing CUDA kernels.
Background with compression, storage systems, networking, and distributed computer architectures.
Data Analytics is one of the rapidly growing fields in GPU accelerated computing. Data preprocessing and engineering are traditionally CPU based and become the bottleneck for ML and DL applications. Complex data analytics pipelines benefit from optimizations in memory management, compression, and parallel algorithms such as sort, search, join, aggregation, group‑by, and scaling across multi‑GPU and multi‑node systems.
Base salary range is $184,000–$287,500 USD for Level 4 and $224,000–$356,500 USD for Level 5. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2025.
NVIDIA is committed to fostering a diverse work environment and is an equal‑opportunity employer. NVIDIA does not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
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Senior Solutions Architect, Data Processing
role at
NVIDIA .
NVIDIA is currently seeking a Solutions Architect for High-Performance Databases. You will research new algorithms and memory management techniques to accelerate databases on modern computer architectures, investigate hardware and system bottlenecks, and optimize performance of data-intensive applications. This role sits at the forefront of technology, providing visibility and impact to a leader like NVIDIA.
NVIDIA has continuously reinvented itself over two decades, starting with the GPU in 1999 that sparked the PC gaming market and revolutionized parallel computing. As a learning machine, NVIDIA constantly evolves to tackle hard problems and amplify human imagination and intelligence.
What You Will Be Doing
Research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications.
Work directly with other technical experts in industry and academia to perform in-depth analysis and optimization of complex data-intensive workloads, ensuring the best possible performance on current GPU architectures.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tool teams at NVIDIA.
Collaborate with industry and academic partners to push the bounds of data processing using NVIDIA’s full product line.
What We Need To See
Masters or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree, or equivalent experience.
8+ years of experience.
Programming fluency in C/C++ with a deep understanding of algorithms and software design.
Hands‑on experience with low-level parallel programming (e.g., CUDA preferred, OpenACC, OpenMP, MPI, pthreads, TBB).
In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.
Domain expertise in high-performance databases, ETL, data analytics, and/or vector database.
Good communication and organization skills with a logical approach to problem solving and prioritization.
Ways To Stand Out From The Crowd
Experience optimizing/implementing database operators or query planners, especially for parallel or distributed frameworks (e.g., production database or Spark).
Background with optimizing vector database index build and/or search.
Experience profiling and optimizing CUDA kernels.
Background with compression, storage systems, networking, and distributed computer architectures.
Data Analytics is one of the rapidly growing fields in GPU accelerated computing. Data preprocessing and engineering are traditionally CPU based and become the bottleneck for ML and DL applications. Complex data analytics pipelines benefit from optimizations in memory management, compression, and parallel algorithms such as sort, search, join, aggregation, group‑by, and scaling across multi‑GPU and multi‑node systems.
Base salary range is $184,000–$287,500 USD for Level 4 and $224,000–$356,500 USD for Level 5. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2025.
NVIDIA is committed to fostering a diverse work environment and is an equal‑opportunity employer. NVIDIA does not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
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